The diagnostic thinking is defined as the process of hypothesis generation and testing. Therefore, the hypotheses generated at the beginning of a physician-patient encounter usually frames and structures the diagnosis, modulating its efficiency and accuracy. The initial hypotheses, although it may be modified by subsequent data, guides the physician's inquiry. The patient interview naturally elicits one or more hypotheses from the beginning. Sometimes a hypothesis is formulated even before the patient interview. This “working hypothesis” constrains not only the rest of the interview, but any subsequent hypotheses generation—which of course must also be tested.
Sometimes, physicians generate a diagnostic hypothesis early in the encounter. In fact, some physicians develop a working hypotheses during the first 50 seconds of a patient consultation. Some studies indicate that physicians form diagnostic hypotheses extremely early in the clinical encounter, and that the mean number of hypotheses under consideration at any time is between two and four.
Since the early generation of hypotheses is, and should be, the rule rather than the exception, it follows that one of the early hypotheses should have a reasonably high probability of being correct, to justify the elaborate system of history taking, physical examination, and the like.
In fact, focusing on an incorrect hypothesis and not considering alternative diagnoses is one of the major causes of diagnostic error. Under basic rules of diagnostic reasoning, within a minutes of a patient encounter (preferably with in 1-2 minutes), a health care provider, namely a physician and/or nurse, should generate at least 2-4 epidemiology-based hypotheses (i.e. rank-ordered hypotheses based on age-sex distribution of disease condition). Differential diagnosis should be heterogeneous or diverse. Diagnostic efficiency and accuracy depends on the quality of the hypotheses generated (i.e. how well the presumed differential diagnoses fits patient signs, symptoms and clinical findings). Experienced physicians usually formulate hypotheses and diagnostic plans very quickly, and the quality of their hypotheses is much better compared to that of novice physicians. Novice physicians often do not know how to generate appropriate hypotheses, they struggle to develop a diagnostic plan, and they have difficulty in establishing diagnostic possibilities from the collection of patient data.
The rank ordering of the generated hypotheses is also very important for effective diagnostic decision making. This rank ordering primarily depends on the epidemiological distribution of disease (determined by patient's age, sex, and clinical characteristics). Expert physicians will likely have an advantage over novices in term of rank ordering differential diagnoses as they learn over the years the distribution of diseases via clinical practice.
Currently, there are books that list all possible disease conditions a patient can have if a single sign or symptom or clinical finding is present. But every disease is related to multiple signs or symptoms or clinical findings and a single sign, symptom or clinical finding is linked to a number of disease or differential diagnoses. Also, these lists of diseases in books or elsewhere will also include diseases that are very rare or uncommon. If someone wants to consider all the available differential diagnoses linked to a given sign, symptom or finding during every patient encounter, the time and costs associated with such a visit would increase leading to increased health care costs, and increasing the risk of diagnostic error and creating an ineffective health care system.
There is no software available to health care providers that can process multiple signs, symptoms and clinical findings to generate a short list of high probability differential diagnoses that are clinically meaningful. Accordingly, a need exists in the art for a system and method that allows health care providers to analyze patient data and generate a high probability differential diagnoses during patient care.